South Asia · Gurmukhi / Shahmukhi
Punjabi Conversational Speech Dataset
Punjabi conversational speech sourced to your specification — no inventory, no fixed listing. This page covers what is specifically hard about this pairing, and which fields your specification needs to pin down.
Why conversational speech in Punjabi is its own problem
The hard part of a natural Punjabi conversation is what the writing system cannot hold. Punjabi is tonal, and tone is not marked in either script, so word pairs that differ only in tone come out identical on the page — the transcript cannot tell them apart, and the annotator is the only channel for that information. Add the dialect split (Majhi around Amritsar and Lahore, Doabi, Malwai and Pwadhi on the Indian side, Multani and Pothohari on the Pakistani side) and a two-speaker recording can carry two dialect systems at once.
The field to pin down first: Fix whether tone-bearing words are written with a tone mark or a phonetic note, and annotate both speakers' dialect region plus side of origin — a transcript without the tone column cannot be aligned back to the audio reliably.
At a glance
| Language | Punjabi |
|---|---|
| Primary region | South Asia |
| Writing system | Gurmukhi / Shahmukhi |
| Category | Conversational Speech |
| Specification field to settle first | Fix whether tone-bearing words are written with a tone mark or a phonetic note, and annotate both speakers' dialect region plus side of origin — a transcript without the tone column cannot be aligned back to the audio reliably. |
| Delivery | Sourced to order, pilot batch before the full run |
What conversational speech data is
Speech from natural conversation between two or more people, on open or semi-structured topics, used for conversational AI, voice assistants, and small talk models.
What buyers get wrong about it
Natural conversation is full of overlapping speech, interruptions, particles, and laughter. Whether to keep these "messy" parts is the first thing to lock down on a project like this.
The specification field that decides the quote
Whether overlapping speech is kept or split — the two outputs cannot be mixed in a single delivery batch.
The language side: what Punjabi demands
Punjabi is the classic case of one spoken language with two scripts: Gurmukhi on the Indian side and Shahmukhi (a Perso-Arabic system) on the Pakistani side. The same passage written on either side cannot be cross-searched against the other.
What we can put in this delivery
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Read and conversational speech
Scripted recording for TTS, and unscripted conversation for recognition. Specified separately because they need different speaker pools.
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Transcription to your convention
Orthographic or phonetic, with the guideline written before production and shared with you for review.
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Speaker metadata
Age band, gender, region and dialect background per file, so you can slice the dataset rather than take it whole.
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Consent documentation
Signed speaker consent covering the intended use, plus collection methodology and the annotation guideline.
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Pilot batch
A small batch first, which you can reject. Misalignments surface after a few hours rather than at delivery.
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Delivery in your format
Audio format, sampling rate, segmentation length and metadata schema set to your pipeline's requirements.
What arrives in a delivery
| Component | What it is |
|---|---|
| Audio files | Format, sampling rate and segmentation length set to your pipeline. Named to a convention you specify. |
| Transcription | Orthographic or phonetic, produced under a guideline you review before production starts. |
| Speaker metadata | Age band, gender, region and dialect background per file, plus a speaker identifier so the dataset can be sliced. |
| Recording conditions | Environment, device and, where relevant, measured signal-to-noise ratio per file. |
| Annotation guideline | The document the annotators worked from, so you can reproduce the conventions on your own data. |
| Consent records | Signed speaker consent covering your intended use, with the transfer mechanism addressed where required. |
| Collection methodology | How speakers were recruited, screened and scheduled — the part that tells you how biased the pool is. |
| Quality report | Pilot outcome, re-work log, and the annotator agreement figures where the task supports measuring them. |
Questions we get about Punjabi Conversational Speech
How many distinct speakers can you provide for Punjabi Conversational Speech?
It depends on the specification and the timeline, and we will give a real number rather than a target. For this pairing, speaker recruitment is usually the step that sets the schedule. Fix whether tone-bearing words are written with a tone mark or a phonetic note, and annotate both speakers' dialect region plus side of origin — a transcript without the tone column cannot be aligned back to the audio reliably.
Can you annotate to our own guideline instead of the default?
Yes, and for this pairing we would recommend it. The hard part of a natural Punjabi conversation is what the writing system cannot hold. That is exactly the kind of decision a default guideline leaves open, and it is where annotators diverge. Send us your guideline, or we will draft one and you can review it before production starts.
Do you offer a sample before we commit to a full run?
Yes. Select a free sample in the request form and describe what you need. A pilot batch is the cheapest way to establish whether the quality bar is reachable for Punjabi Conversational Speech before committing to the full volume.
Is the data licensed or owned outright?
Licensing terms are set per project, so tell us how the model will be used and whether it will be distributed. Consent documentation travels with the data either way, and we do not handle medical or clinical data or recorded telephone calls.
Other datasets in Punjabi
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Punjabi Speech Commands
Targeted recordings of short command words or phrases, usually with many speakers reading each entry several times over, used for wake words and on-device command recognition.
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Punjabi Read Speech
Recordings of speakers reading specified text, with clear pronunciation and known text, the base material for TTS and ASR.
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Punjabi Podcast Speech
Long-form podcast and interview audio, either solo monologue or two-person conversation, used for long-form speech recognition and speaker modeling.
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Punjabi Multilingual Speech
Speech data covering multiple languages within one project, used for multilingual ASR, cross-lingual transfer, and language identification.
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Punjabi Noisy Speech
Speech collected under background noise — street, in-car, restaurant, office and other real environments — used for noise-robust models and speech enhancement.
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Punjabi Code-Switching Speech
Speech that mixes two or more languages inside a single utterance — Hinglish, Spanglish, Taglish — used for recognition in real spoken settings.
Conversational Speech in other languages
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Hindi Conversational Speech
South Asia
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Arabic (MSA) Conversational Speech
Middle East & North Africa
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Indonesian Conversational Speech
Southeast Asia
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Thai Conversational Speech
Southeast Asia
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Turkish Conversational Speech
Middle East & Europe
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Vietnamese Conversational Speech
Southeast Asia
Request Punjabi Conversational Speech
Tell us the language, the hours, and what the data needs to look like. You will get a real number and a real timeline — not a range. If we cannot source it well, we will tell you that instead.
- Pilot batch before the full run, so problems surface early.
- Consent documentation delivered with the data.
- No medical or clinical data. No recorded telephone calls.